1 Getting Started
1.5 Some case studies
CASE STUDY 1: Paperware company
Problem: Want forecasts of each of hundreds of items. Series can be stationary, trended or seasonal. They currently have a large forecasting program written in-house but it doesn’t seem to produce sensible forecasts. They want me to fix it.
Additional information
- Program written in COBOL making numerical calculations limited. It is not possible to do any optimisation.
- They employ no statisticians and want the program to produce forecasts automatically.
CASE STUDY 1: Paperware company
Methods currently used
- A
-
12 month average
- C
-
6 month average
- E
-
straight line regression over last 12 months
- G
-
straight line regression over last 6 months
- H
-
average slope between last year’s and this year’s values. (Equivalent to differencing at lag 12 and taking mean.)
- I
-
Same as H except over 6 months.
- K
-
I couldn’t understand the explanation.
CASE STUDY 2: PBS
CASE STUDY 2: PBS
The Pharmaceutical Benefits Scheme (PBS) is the Australian government drugs subsidy scheme.
- Many drugs bought from pharmacies are subsidised to allow more equitable access to modern drugs.
- The cost to government is determined by the number and types of drugs purchased. Currently nearly 1% of GDP.
- The total cost is budgeted based on forecasts of drug usage.
CASE STUDY 2: PBS
CASE STUDY 2: PBS
- In 2001: $4.5 billion budget, under-forecasted by $800 million.
- Thousands of products. Seasonal demand.
- Subject to covert marketing, volatile products, uncontrollable expenditure.
- Although monthly data available for 10 years, data are aggregated to annual values, and only the first three years are used in estimating the forecasts.
- All forecasts being done with the function in MS-Excel!
CASE STUDY 3: Car fleet company
Client: One of Australia’s largest car fleet companies
Problem: how to forecast resale value of vehicles? How should this affect leasing and sales policies?
- They can provide a large amount of data on previous vehicles and their eventual resale values.
- The resale values are currently estimated by a group of specialists. They see me as a threat and do not cooperate.
CASE STUDY 4: Airline
CASE STUDY 4: Airline
CASE STUDY 4: Airline
Problem: how to forecast passenger traffic on major routes?
- They can provide a large amount of data on previous routes.
- Traffic is affected by school holidays, special events such as the Grand Prix, advertising campaigns, competition behaviour, etc.
- They have a highly capable team of people who are able to do most of the computing.